Search Results (206)

Accurate measurement of plant height in leafy vegetables is challenging due to their short stature, high planting density, and severe canopy occlusion during later growth stages. These factors often limit the reliability of single-plant monitoring across the full growth cycle in open-field environments. To address this, we propose a multi-temporal point cloud alignment method for accurate plant height measurement, focusing on Choy Sum (Brassica rapa var. parachinensis). The method estimates plant height by calculating the vertical distance between the canopy and the ground. Multi-temporal point cloud maps are reconstructed using an enhanced Oriented FAST and Rotated BRIEF–Simultaneous Localization and Mapping (ORB-SLAM3) algorithm. A fixed checkerboard calibration board, leveled using a spirit level, ensures proper vertical alignment of the Z-axis and unifies coordinate systems across growth stages. Ground and plant points are separated using the Excess Green (ExG) index. During early growth stages, when the soil is minimally occluded, ground point clouds are extracted and used to construct a high-precision reference ground model through Cloth Simulation Filtering (CSF) and Kriging interpolation, compensating for canopy occlusion and noise. In later growth stages, plant point cloud data are spatially aligned with this reconstructed ground surface. Individual plants are identified using an improved Euclidean clustering algorithm, and consistent measurement regions are defined. Within each region, a ground plane is fitted using the Random Sample Consensus (RANSAC) algorithm to ensure alignment with the X–Y plane. Plant height is then determined by the elevation difference between the canopy and the interpolated ground surface. Experimental results show mean absolute errors (MAEs) of 7.19 mm and 18.45 mm for early and late growth stages, respectively, with coefficients of determination (R²) exceeding 0.85. These findings demonstrate that the proposed method provides reliable and continuous plant height monitoring across the full growth cycle, offering a robust solution for high-throughput phenotyping of leafy vegetables in field environments. Full article

To achieve global carbon-neutrality goals, magnetic levitation (maglev) technologies offer a promising pathway toward sustainable, energy-efficient transportation systems. In this study, a comprehensive methodology was developed to analyse and optimise the levitation performance of high-temperature superconducting (HTS) maglev systems. Several permanent magnet guideway (PMG) configurations were compared, and an optimised PMG Halbach array design was identified that enhances flux concentration and significantly improves levitation performance. To accurately model the electromagnetic interaction between the HTS bulk and the external magnetic field, finite element models based on the H-formulation were established in both two dimensions (2D) and three dimensions (3D). An HTS maglev demonstrator was built using YBCO bulks, and an experimental platform was constructed to measure levitation force. While the 2D model offers fast computation, it shows deviations from the measurements due to geometric simplifications, whereas the 3D model predicts levitation forces for the cylindrical bulk with much higher accuracy, with errors remaining below 10%. The strong agreement between experimental measurements and the 3D simulation across the entire force–height cycle confirms that the proposed model reliably reproduces the electromagnetic coupling and resulting levitation forces in HTS maglev systems. The paper provides a practical and systematic reference for the optimal design and experimental validation of HTS bulk-based maglev systems. Full article

Resistance against water penetration is one of the key indicators of concrete durability in humid and pressurized environments. An intelligent model based on the XGBoost machine-learning algorithm was developed to predict the water penetration depth, using 1512 independent experimental measurements. The influential variables included water pressure, pressure duration, thermal cycles, fiber content, curing, and compressive strength. The investigated concrete specimens and field-tested structures in this study were exposed to arid and hot climatic conditions, and the proposed model was developed within this environmental context. To accurately simulate the water transport behavior, a cylindrical-chamber test was employed, enabling non-destructive and in-situ evaluation of structures. Correlation analysis revealed that compressive strength had the strongest negative influence (r = −0.598), while free curing exhibited the strongest positive influence (r = +0.654) on penetration depth. After hyperparameter optimization, the XGBoost model achieved the best performance (R² = 0.956, RMSE = 1.08 mm, MAE = 0.81 mm). Feature importance analysis indicated that penetration volume, pressure, and curing were the most significant predictors. According to the partial dependence analysis, both pressure and duration exhibited an approximately linear increase in penetration depth, while a W/C ratio below 0.45 and curing markedly reduced permeability. Microstructural interpretation using MIP, XRD, and SEM tests supported the physical interpretation of the trends identified by the machine-learning model. The results demonstrate that machine-learning-models can serve as fast and accurate tools for assessing durability and predicting permeability under severe environmental conditions. Finally, the permeability of several real structures was evaluated using the machine-learning approach, showing excellent prediction accuracy. Full article

This paper reviews the research progress of supercapacitors (SCs), including the influence of electrode materials on energy storage mechanism and performance, and life prediction. Supercapacitors show application potential in many fields due to their high-power density, fast charge–discharge capability, long cycle life, and environmental protection characteristics. In this paper, the energy storage mechanism of the double-layer capacitor, pseudocapacitor, and asymmetric supercapacitor are discussed. New electrode materials, such as carbon-based materials, metal oxides, and conductive polymers, are reviewed based on the performance optimization measures that are involved in the microstructure design of electrode materials, and integrate the rule prediction of supercapacitors into comprehensive learning. When designing and using supercapacitors, we should not only pay attention to their life but also pay attention to their remaining service life in real time. The paper also mentions the progress of life prediction technology, which is of great significance to improve the reliability and maintenance efficiency of energy storage equipment, and ensure the long-term stable operation of energy storage systems. Future research directions include increasing energy density, extending life, adapting to extreme environments, developing flexible and wearable devices, intelligent management, and reducing costs. Full article

This work presents a dynamic flowsheet model that predicts residual stress from shot peening. The peening medium is characterized by size and shape, and evolves dynamically with abrasion, fracture, classification, and replenishment. Because particle size and impact location vary stochastically, the resulting residual stress field is spatially heterogeneous. Residual stress fields are predicted in real time through a convolutional long short-term memory (ConvLSTM) neural network trained on finite element simulations, enabling fast, mechanistically grounded prediction of surface stress evolution under industrial shot peening conditions. We deploy the model in a pair of 10,000-cycle production peening case studies, demonstrating that media recharge strategy has a measurable effect on residual stress outcomes. Full article

Zeolite is a popular soil amendment capable of improving physical and chemical properties of soils. This study investigates how zeolite concentration affects the hydrological connectivity of sandy loam soil. Soil samples with different zeolite concentrations C_z (0, 1, 1.5, 2.5, 5, 10, 15, and 30%) were analyzed for changes in water dynamics through Fast Field Cycling Nuclear Magnetic Resonance (FFC-NMR) relaxometry. FFC-NMR data revealed that the investigated zeolite can modify the pore size distribution in a wide range (1–15%) of C_z, as the zeolite particle size distribution has a percentage of coarse particles (56%) appreciably higher than that of the original soil (37%). Moreover, a concentration of 1% produces a more relevant increase in the soil’s meso- and macropores, while for C_z > 1.5%, the change in pore size distribution is damped by the increase in water retention that occurs upon increasing zeolite concentration. The analysis also demonstrated that C_z = 1% is sufficient to achieve the highest values of both structural and functional connectivity indexes. In conclusion, for sandy loam soil, adding a zeolite concentration of 1% is sufficient to improve the soil’s physical characteristics, with significant effects on soil hydrological behavior, and can be considered a valid practice to manage the addition of a water resource to the soil. Full article

Spatial heterogeneity of species distributions modulates local interactions and dynamics, playing a key role in the development of diversity and ecosystem functioning during secondary succession. Here, we tested the cycling heterogeneity hypothesis, which predicts fluctuating spatial beta diversity, i.e., alternating periods of high and low heterogeneity during succession, driven by the changes in the abundance of dominant species. We analyzed long-term monitoring data collected annually along 52 m long permanent transects over 15 years in abandoned fields. Recovery of grassland vegetation was fast due to the humus-rich chernozem soil, the rich species pool, and the fast colonization of native grassland species from adjacent natural meadow steppe. Heterogeneity was quantified by spatial beta diversity as the mean pairwise dissimilarity among sampling units. Incidence-based (Jaccard) and abundance-based (Bray–Curtis) indices were used. We found large temporal fluctuations in spatial heterogeneity, with amplitudes reaching 80–100% of the total beta diversity range across the successional gradient. Two major beta diversity peaks were identified: maximum heterogeneity occurred during transitions between successional phases, whereas periods of minimum heterogeneity coincided with the sequential dominance of a few particular species. Bromus sterilis and Festuca valesiaca were the most important species driving heterogeneity. Similar patterns were recorded at two monitoring sites. Changing the sampling unit size computationally, varying the dissimilarity indices, or excluding dominant species had little influence on the results. Using null models, we removed the effects of species richness and abundance and found an increasing degree of spatial dependence as succession progressed. However, the corresponding beta deviations also showed non-linear, fluctuating patterns. Our results support the cycling heterogeneity hypothesis in secondary grassland succession. Increasing understanding of heterogeneity patterns provides new opportunities to optimize the temporal and spatial design of grassland restoration measures. Full article

Jellyfish biohybrid robots have been demonstrated to be successfully programmed to perform vertical sampling profiles of the ocean water column. However, the jellyfish’s endogenous swimming behavior can interfere with the controlled swim cycles, decreasing performance. Further, the model animal used to date, Aurelia aurita, is a relatively slow, weakly swimming species. To enhance the performance of the biohybrid vehicles, we tested whether removing the swimming pacemaker of the jellyfish, the rhopalia, eliminated endogenous movements and enhanced responsiveness of the jellyfish to the swim controller. Further, we tested the responsiveness of two fast-swimming jellyfish species, the rhizostome Cassiopea spp. and the cubomedusae Alatina alata. We found in field trials, where the jellyfish swam controlled vertical profiles in the ocean, that removal of rhopalia eliminated all endogenous behaviors and greatly improved the responsiveness of the jellyfish to the swim controller. This was especially true for species with strong endogenous behaviors that prevented the controller from manipulating swim pulses. Further, we found that both Cassiopea spp. and A. alata were highly responsive to the swim controller and that these faster-swimming jellyfish species greatly increased the speed at which the biohybrid vehicle could traverse vertical profiles in the water column. These enhancements greatly increase the reliability and versatility of jellyfish biohybrid robot vehicles. Full article

The energy that powers electric vehicles comes directly from their high-performance batteries, serving as the heart of their operation. They convert stored chemical energy into mechanical energy to propel vehicles. One of the most vital parts of an electric vehicle is a battery pack. Superior advantages such as higher energy density, longer life cycles, and the fast-charging ability of lithium-ion batteries set them apart from the others. However, battery performance and longevity exhibit a high degree of temperature sensitivity. In other words, operating batteries below and above the specified temperature range values causes problems such as decreased lifespan, safety issues, and performance losses. In electric vehicles, varying power demands during driving cause different current levels to be drawn from the battery packs. This leads to fluctuations in battery temperatures due to chemical reactions occurring. Besides that, regional and seasonal temperature variations also affect the operating temperatures of batteries. Therefore, maintaining the batteries within the specified temperature range, typically between 25 and 40 °C, is only achievable with an adequate battery thermal management system. This review intends to guide researchers working on designing more efficient thermal management systems by providing refined information about previous efforts in this field. The designs found in the literature have been illustrated with simplified figures. Cooling inlet and outlet locations are indicated in blue and red, enabling easier comparison and better understanding of different cooling designs. Air-cooling studies in the literature show that a well-designed system can keep the T_max and ΔT values of LiB cells ~305 K and 2.8 K during 3C discharge at a T_ambient of about 298.15 K. When liquid cooling systems are examined, a 50% glycol–water mixture can maintain pouch cells at nearly 30.3 °C with a ΔT of 2.78 °C under similar 3C and 25 °C conditions. Overall, the results demonstrate that well-designed BTMS configurations including optimized airflow or coolant–flow arrangements are capable of keeping LiBs safely within their optimal thermal operating conditions. Full article

High-efficiency, lead-free dielectrics are sought for pulsed-power capacitors, yet pristine Bi_0.5Na_0.5TiO₃ (BNT) suffers from large remanence, high coercivity, and limited breakdown strength. Here, we report (1 − x)Bi_0.5Na_0.5Ti_0.97Nb_0.03O₃-xSr_0.85Ba_0.15Ta_0.5+0.02xAl_0.5−0.02xO₃ (BNTNb–SBTA, x = 0–0.15) ceramics synthesized via solid-state reaction, achieving enhanced relaxor ferroelectric behavior through multi-cation substitution at A- and B-sites. X-ray diffraction confirms a pure perovskite solid solution, while scanning electron microscopy reveals grain refinement, suppressing oxygen vacancies and boosting the breakdown strength. Raman and dielectric analyses evidence strengthened relaxor behavior, accompanied by loop slimming and a systematic rise in breakdown strength. The composition x = 0.10 achieves the best trade-off, delivering W_rec = 3.357 J cm⁻³ and η = 90.5% at E_b = 240 kV cm⁻¹. Robust operational stability is demonstrated with small variations of W_rec/η over 0.1–200 Hz, 25–175 °C, and 10⁶ cycles. Pulsed tests show fast discharge (∼26 ns) with W_d = 0.826 J cm⁻³ at ∼90% efficiency under moderate fields. These results indicate that synergistic A/B-site disorder (Sr/Ba on A-site; Ta/Al with Nb on B-site), combined with microstructural densification, effectively minimizes P_r while elevating E_b, enabling high-efficiency energy storage under practical operating conditions. Full article

Magnetic Resonance Relaxometry is a powerful technique that reveals a sample’s molecular dynamics thanks to the dependence of the T₁ relaxation time on field strength. With applications in protein research, food systems, material development, and environmental science, relaxometry measurements are typically undertaken using a technique known as fast field cycling, where T₁ is measured at a range of detection fields. However, the sample experiences relaxation in a variable field without the challenges associated with retuning a probe to each of the necessary frequencies of interest. This technique is limited by a maximum relaxation time, since the measurement and relaxation fields are typically applied using a fluid-cooled electromagnet, which will ultimately overheat for very long experimental times. In this work, we propose an alternative approach to permit measurements of samples with inherently long T₁ values. We utilise a broadband spectrometer alongside a solenoid transmit-receive coil and custom tuning and matching boards, whilst two sets of magnets are moved around the coil, to achieve a range of different fields. By collecting a reduced number of points and utilising this method, we show it is still possible to make useful measurements on samples at a range of frequencies, which has great potential in quality assurance applications. We find a similar trend for food samples of corn oil, while manganese chloride, a common contrast agent, has more than a 100% difference when compared to traditional fast field cycling measurements. Full article

There is a critical demand for flexible resistive sensors that combine high sensitivity with a wide linear range, fast response speed, and excellent long-term stability. This study presents the development of a high-performance resistive flexible sensor utilizing graphene-coated iron nanowires (Fe NWs@Graphene) as conductive fillers within a polyurethane sponge (PUS) substrate. The sensor was constructed with a sandwich-like structure, consisting of Fe NWs@Graphene-impregnated PUS as the sensing layer, encapsulated by polydimethylsiloxane (PDMS) for protection. The Fe NWs were synthesized via a chemical reduction process employing an external magnetic field. Subsequent chemical vapor deposition enabled uniform graphene coating on the surface of Fe NWs. Systematic performance assessments demonstrated that the Fe NWs@Graphene flexible sensor exhibits a gauge factor (GF) of 14.5 within a 0–100% strain range, representing a 71% improvement over previously reported Fe NW-based strain sensors, along with excellent linearity (R² = 0.994). The sensor also showed rapid response times (113 ms for loading and 97 ms for unloading) and outstanding cyclic stability over 3000 stretching cycles at 50% strain. These enhancements are attributed to the synergistic effects between Fe NWs and graphene: the graphene shell effectively protects the Fe NW core against oxidation, thereby improving stability, and facilitates efficient charge transport, while the Fe NWs serve as bridging agents that improve both mechanical integrity and electrical percolation. In addition, application tests simulating human motion detection confirmed the sensor’s ability to accurately capture muscle-induced strain signals with high repeatability. The results underscore the feasibility of Fe NWs@Graphene as conductive fillers for high-sensitivity, wide-range, and stable flexible sensors, highlighting the potential in wearable electronics and human–machine interaction systems. Full article

Redox flow batteries (RFBs) are an emerging class of large-scale energy storage devices, yet the commercial benchmark—vanadium redox flow batteries (VRFBs)—is highly constrained by a modest open-circuit potential (1.26 V) while posing an expensive and volatile material procurement costs. This review focuses on recent progress in diversifying redox-active species to overcome these limits, highlighting chemistries that increase overall cell voltage, energy density, and efficiency while maintaining long cycle life and safety. The study dwells deeper into manganese-based systems (e.g., Mn/Ti, Mn/V, Mn/S, M/Zn) that leverage Mn’s high positive potential while addressing Mn(III) disproportionation reactions; iron-based hybrids (Fe/Cr, Fe/Zn, Fe/Pb, Fe/V, Fe/S, Fe/Cd) that exploit the low cost, and its abundance, along with membrane and electrolyte strategies to prevent the potential issue involving crossover; cerium-anchored catholytes (Ce/Pb, V/Ce, Eu/Ce, Ce/S, Ce/Zn) that deliver high operational voltage by implementing an acid-base media, along with selective zeolite membranes; and halide systems (Zn–I, Zn–Br, Sn–Br, polysulfide–bromine/iodide) that combine fast redox kinetics and high solubility with advances such as carbon-coated membranes, bromine complexation, and ambipolar electrolytes. Across these various families of RFBs, the review highlights the modifications made to the flow-fields, membranes, and electrodes by utilizing a zero-gap serpentine flow field, sulfonated poly(ether ether ketone) (SPEEK) membranes, carbon-modified and zeolite separators, electrolyte additives to enhance the voltage (VE%), and thereby energy (EE%) efficiency, while reducing the overall system cost. These modifications to the existing RFB technology offer a promising alternative to traditional approaches, paving the way for improved performance and widespread adoption of RFB technology in large-scale grid-based energy storage solutions. Full article

Nigeria’s aquaculture sector, which has been dominated by the production of African catfish (Clarias gariepinus), has held considerable potential to improve national food security, support livelihoods, and contribute to economic growth. Although Nigeria has been ranked among the world’s leading producers of farmed catfish, a persistent fish supply deficit that exceeds 2.5 million metric tons annually has been reported. This gap has been sustained by factors such as low productivity, genetic decline, inadequate hatchery systems, and limited export competitiveness. A comprehensive perspective is presented in this review, in which findings from recent researches, field surveys, and stakeholder consultations have been synthesized. The dominance of hybrid species such as Heteroclarias, which has been driven by consumer demand due to fast growth and large body size, is highlighted. Additionally, ecological and genetic concerns resulting from unregulated breeding are emphasized. Major systemic constraints, which include poor broodstock management, weak hatchery infrastructure, low technical capacity, and poor supply chain governance, have also been identified. A strategic approach involves modernizing fish breeding programs by developing a robust and active Fish Breeding Community of Practice (FCoP), enhancing physical infrastructure, improving data collection and management, standardizing germplasm exchange procedures, and increasing the number and capacity of fish breeders and technicians in breeding programs. Identifying traits preferred by farmers and end-users ensures that fish breeding is demand-driven and inclusive. Building capacity in genomic resources to implement an accurate predictive platform for performance assessment will significantly shorten the breeding cycle and increase the rate of genetic progress. This will be complemented by the adoption of modern aquaculture technologies, such as recirculating aquaculture systems, and the development of institutional frameworks for production, certification, and traceability schemes. Capacity development, which should be promoted through collaboration among academic institutions, industry actors, and government agencies, has been recommended. The alignment of aquaculture expansion with environmental sustainability, improved biosecurity, and habitat protection has been considered critical. By outlining strategies for innovation, investment, and policy reform, this review provides a roadmap through which Nigeria’s catfish industry can be transformed into a globally competitive and sustainable sector. Full article

In this study, two novel hybrid monomers (4BD-EDOT and 3BD-EDOT) containing a biphenyl group and a 3,4-ethylenedioxythiophene (EDOT) unit were synthesized and polymerized electrochemically in a CH₂Cl₂-Bu₄NPF₆ electrolyte solution. Characterizations of the resulting P4BD-EDOT and P3BD-EDOT were studied by CV, scanning electron microscopy (SEM), and spectroelectrochemistry in order to examine the effect of different substitution positions of biphenyl on the electrochromic performance of the resultant hybrid polymers. Both polymers have favorable redox activity (a distinct redox peak) and good redox stability (55–49% electroactivity was retained after 1000 cycles). The spectro-electrochemistry study found that both show a distinct color change from reddish brown to blue/purple for P4BD-EDOT with a lower band gap (1.54 eV) and from transparent color to light blue for P3BD-EDOT with a larger band gap (1.73 eV). These electrochromic polymer films also have fast switching speed (0.5–0.2 s), with the favorable optical contrast (22.6% at 1100 nm for P4BD-EDOT) and decent coloration efficiency (250.4 cm² C⁻¹ at 780 nm for P3BD-EDOT). All these results show that both monomers have important values related to the electrochromic field. This work also shows that the different substitution positions of the biphenyl unit affect the spectroelectrochemistry and electrochromic characteristics of the resultant hybrid polymers. Full article